搜索结果: 1-15 共查到“理论统计学 regression models”相关记录27条 . 查询时间(0.109 秒)
Comparison of nonhomogeneous regression models for probabilistic wind speed forecasting
Comparison nonhomogeneous regression models probabilistic wind speed forecasting
2013/6/14
In weather forecasting, nonhomogeneous regression is used to statistically postprocess forecast ensembles in order to obtain calibrated predictive distributions. For wind speed forecasts, the regressi...
Additive inverse regression models with convolution-type operators
Inverse regression Additive models Convolution-type operators Mathematical subject codes: primary 62G08 secondary 62G15 62G20
2013/4/27
In a recent paper Birke and Bissantz (2008) considered the problem of nonparametric estimation in inverse regression models with convolution-type operators. For multivariate predictors nonparametric m...
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Total loss estimation using copula-based regression models
dependence modeling generalized linear model number of claims claim size policy loss
2012/11/23
We present a joint copula-based model for insurance claims and sizes. It uses bivariate copulae to accommodate for the dependence between these quantities. We derive the general distribution of the po...
Empirical process of residuals for regression models with long memory errors
Empirical process of residuals regression models
2011/3/24
We consider the residual empirical process in random design regression with long memory errors. We establish its limiting behaviour, showing that its rates of convergence are different from the rates ...
Beta-binomial/gamma-Poisson regression models for repeated counts with random parameters
bivariate counts longitudinal data overdispersion random effects regressionmodels
2010/3/11
Beta-binomial/Poisson models have been used by many authors to model multivariate
count data. Lora and Singer (Statistics in Medicine, 2008) extended such models
to accommodate repeated multivariate...
Bayesian predictive densities for linear regression models under alpha-divergence loss：some results and open problems
shrinkage prior Bayesian predictive density alpha-divergence Stein effect
2010/3/10
This paper considers estimation of the predictive density for
a normal linear model with unknown variance under -divergence loss for
−1 1. We first give a general canonical form for the...
Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models
Adaptive estimation Heteroscedastic regression Nonasymptoticestimation Nonparametric estimation Oracle inequality
2010/3/10
An adaptive nonparametric estimation procedure is constructed
for heteroscedastic regression when the noise variance depends on the
unknown regression. A non-asymptotic upper bound for a quadratic
...
Conditional least squares estimation in nonstationary nonlinear stochastic regression models
Stochastic nonlinear regression heteroscedasticity nonstation-ary process time series branching process conditional least squares estimator quasi-likelihood estimator
2010/3/9
National Agronomical Research Institute (INRA)
Let {Zn} be a real nonstationary stochastic process such that
E(Zn|Fn−1)a.s.< 1 and E(Z2n |Fn−1)a.s.< 1, where {Fn} is an increas-
ing seq...
Sequentially Updated Residuals and Detection of Stationary Errors in Polynomial Regression Models
Autoregressive unit root Change-point Control chart Nonparametric smoothing Sequential analysis Weighted partial sum process
2010/3/9
The question whether a time series behaves as a random walk or as a stationary
process is an important and delicate problem, particularly arising in financial statistics,
econometrics, and engineeri...
Post-L1-Penalized Estimators in High-Dimensional Linear Regression Models
Post-L1-Penalized Estimators High-Dimensional Linear Regression Models
2010/3/9
In this paper we study the post-penalized estimator which applies ordinary,
unpenalized linear regression to the model selected by the first step penalized estimators,
typically the LASSO. It is wel...
Geographically Assisted Elicitation of Expert Opinion for Regression Models
elicitation expert opinion regression
2009/9/22
One of the perceived strengths of Bayesian modelling is the ability to
include prior information. Although objective or noninformative priors might be
preferred in some situations, in many other app...
On the bootstrapping heteroscedastic regression models
Bootstrap heteroscedastic regression ordinary least squares estimates
2009/9/21
The distributjons of deviations of point estimators for
parameters of iterest are essential in the evvaluation of the eficiency of
point estimators. The bootstrap method suggested by B. Efron is on...
Almost sure properties of weighted vectorial martingales transforms with applications to prediction for linear regression models
least squares estimators cumulative prediction and estimation Linear regression models
2009/9/21
We establish new almost sure properties for powers of
weighted martingale transbrms. It allows us to deduce usefuI asymptotic
results for cumulative prediction and estimation errors associated
with...